Dissertations and Theses @ UNI
Availability
Open Access Thesis
Keywords
Data warehousing;
Abstract
The database community is devoting increasing attention to the research themes concerning data warehouses. After having invested a lot of time and resources to build huge and complex information systems, managers ask for support in obtaining quickly summary information to help in planning and decision making. Data warehousing systems address this issue by enabling managers to acquire and integrate information from different sources and to query efficiently very large databases. Building a data warehouse requires adopting design and implementation techniques completely different from those underlying information. Multidimensional data structures used for decision support applications in data warehouses have rather different requirements to data modeling techniques. In case of operational systems the data models are created from application specific requirements. The data models in data warehouses are based on the analytical requirements of the users. Furthermore, the development of data warehouse structures requires the consideration of user-defined information requirements as well as the underlying operational source systems. This paper first reviews background and literature on data warehousing, follows with a description of the two dominant data modeling techniques: ER modeling and dimensional modeling. It then points out their differences and similarities, as well as the evaluation of these two modeling techniques.
Year of Submission
2000
Degree Name
Master of Science
Department
Department of Computer Science
First Advisor
Walter E. Beck
Second Advisor
John W. McCormick
Third Advisor
Kevin C. O'Kane
Date Original
2000
Object Description
1 PDF file (71 leaves)
Copyright
©2000 Litao Fu
Language
en
File Format
application/pdf
Recommended Citation
Fu, Litao, "An Evaluation of Two Different Data Modeling Techniques for Data Warehousing" (2000). Dissertations and Theses @ UNI. 2705.
https://scholarworks.uni.edu/etd/2705
Comments
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